Structuring data gathering on organic farms:

Subtitle:the transdisciplinary development and use of a farm scan within a broader methodological framework

In Flanders, organic suckler cow farmers meet at a regular basis to exchange experiences and knowledge. Within this network, an advisory service is involved to give advice on multiple aspects of the farming system. Research has shown that network organisation is rewarding to gain access to knowledge, to facilitate learning processes, and to foster knowledge creation (Van Wijk et al., 2003). Although effective management is linked to well-designed monitoring and evaluation (Stem et al., 2005), decision making of the farmers in this network is mainly based on practical experiences and perceptions. Comparable data and knowledge gathering by the farmers is lacking due to several reasons. For example, their accountancy systems differ. Furthermore, each farm is characterized by specific conditions. As a result, the farmers themselves are not able to organize efficient data collection to share within their network. However, monitoring and evaluation forms the basis for improved decision making and improved management. Therefore, this study aims at the development of a monitoring and evaluating approach to improve decision making on organic beef farms. Through the use of a farm scan, we aim at gathering and structuring farm specific data in an efficient way to systemically examine interventions and to share this knowledge within their network. The development of farm scan is part of a broader methodological framework, which focusses on a system based, transdisciplinary approach. The system based approach aims at integrating knowledge on the complex relations within organic farms. The transdisciplinary approach focusses on the involvement of farmers, researchers and advisory services to facilitate the knowledge co-creation between stakeholders and scientists. A mixture of both quantitative and qualitative techniques for data collection are at the basis of this methodological framework and are described in depth by Marchand et al. (2015). In this paper, we focus on the iterative farm scan development and use in practice and discuss the experiences within the broader methodological framework.

Publication year:2015